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Key Trends In Digital & Analytics In 2015

Retailers will increasingly adopt multiple IoT technologies in the coming years to reshape the customer experience, to drive loyalty and to focus on inventory

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Real-time Customer engagement/interactions - There is shift from determining the proactive offers / next best offers from simple cookie based or click stream based analytics to more valued, analytical, data enriched analysis. This integrates the customer behavior patterns coming from other data sources / historical transactions. There is a wave of technology adoption for responding customers in real-time with more meaningful offers. The trend needs powerful processing platform with capability to handle high volume of data with very high velocity. Enterprises are either evaluating or adopting the big data platforms for the same. We will see more adoption of the big data platform in 2016.

Cashless payments and related analytics
- There is a great adoption of cashless payment methods (online, payment wallets, etc.) in India. The adoption will improve over time. Most of the cashless payment methods have ability for further improve the customer acquisition by extending appropriate offers. Analytics will play a great role in determining the offers that can be extended to these methods.

Telecom transformation due to 4G - Introduction to 4G services will cause disruptive adoption of mobile internet in India. Companies like Bharati and Reliance are geared up to swipe the 4G market. The introduction of the 4G services provide a great challenge to the service providers to handle the generated huge volume of data effectively. It is estimated that there will be around 30-40 TB of data that will get generated on daily basis. Telecom service providers need to gear-up to manage and handle this data and use it for their benefits. The QoS parameters and analytics will also play a great role from regulation perspective to ensure the quality of service.

Shift from 'Data as a Service' to 'Analytics as a Service'
- The trend started with off-loading the data processing services to the private cloud or to the hosted environment and then derive the intelligence in local data center using Analytics solutions. Customers are now looking to avail the analytics as a service solutions. Niche companies or the companies with rich domain expertise are now providing analytics as a service in collaboration with IaaS vendors.

Adoption of Big Data platforms - During past couple of years many customers evaluated the new/emerging technologies/platforms required to handle the structure and unstructured data. During second half of 2015 we observed that many customers start adopting the big data solutions/platform. The trend will continue and grow further in 2016. Many customers also have adopted the 'Data Lake' strategy for starting the Big Data initiatives. Customer are taking the staggered approach to build the data lakes and at the same time identifying the analytics initiatives that can be derived out of data collected in the data lake.

IoT Devices, Human and Machine Interface - There were many enquiries and evaluation happening on adoption of data generated through IoT devices like Fitbit, Nike Fuelband, Apple Watch, Heat Sensors, etc. The blueprints are getting defined for integrating the IoT data into generic Analytics platform and derive meaningful intelligence out of it. Customers are also evaluating the scope KPO automation through Human and Machine interfacing solutions. The solutions use the technology for audio, video, images, text and other unstructured data analytics.

Key Trends in 2015: Retail Analytics

Retailers are increasingly using omni channel marketing to improve the customer experience as they shop across various channels like store, web and mobile platforms. There has been a huge growth in cross channel data volume and now Retailers have access to variety of data which include not only the demographic information but also past purchases, call centre interaction, social media interaction etc.

Retailers are leveraging analytics tools to enhance customer loyalty by creating a personalised shopping experience that customises coupons and offers to match customers' needs.

Retailers are increasingly using segmentation based on purchase patterns, price sensitivity and customer lifestyle to identify the most relevant customers for targeting, which results in more relevant offers. Segmentation helps focus marketing on the customers who will most likely buy the products or services and avoid markets which will not be profitable.

Retailers are adjusting their product mix from store to store based on the preferences of their customers. This help retailers improve their inventory allocations by understanding customer demand and their choice patterns resulting in increased revenues and margins.

Using analytics, retailers are able to determine the optimal pricing of products and services. The price elasticity not only help in only finding identifying the products that are most and least price sensitive but can also be used with optimisation to identify the optimal pricing.

Increasingly number of companies are adopting open source analytical tools to provide descriptive, prescriptive and predictive analysis of the fast increasing volumes of data which are both structured and unstructured in nature in order to reduce the total cost of ownership.

More retailers are introducing mobile apps for integrated loyalty programs. Consumers no longer have to clutter their wallets with physical cards anymore. Instead, they can use their smartphones to track and redeem their rewards through mobile applications.

Emerging Trends to watch out for in 2016: Retail Analytics

Fraud detection and prevention will be an important concern for retailers looking to build security and preserve consumer trust. Using analytics, retailers can identify unusual patterns of product and inventory movement.

Radio-frequency identification (RFID) tags and readers will increasingly provide substantially more data on product movements and locations for retailers to analyse. Retailers will be using analytics to optimise their inventory and reduce their transportation costs.

Workforce analytics will help organizations effectively plan their future workforce needs to increase labour efficiency and improve schedule effectiveness. Analytical tools would be used for workforce acquisition and labour scheduling based on when customers are most likely to visit a store.

Retailers will increasingly adopt multiple IoT technologies in the coming years to reshape the customer experience, to drive loyalty and to focus on inventory. The use cases in retail will include sensors on products, interactive consumer engagement, automated store lighting, shopper intelligence, perishable tracking, fleet operations tracking etc.

There will be an increase in video analytics as powerful processors are becoming available at affordable price points to video surveillance manufacturers. Video surveillance with analytical models can be used for effective in store promotions, stock out analysis and tracking customer movement inside the store.


Rise and growth of e- commerce or digitisation of retail has been one of the key trends in the retail sector. As this digitisation continues in the new year, companies will turn to analytical solutions to both manage and make sense of the huge amount of data being churned from these transactions. Companies will require insights into the consumer behaviours to try and personalise user experience as competition will hot up between various e-commerce retailers.

These companies are already investing in significant social media management to promote their services and will also turn to analytics to gain insight from that data regarding their product perception and target market. App based analytics solutions will be at the forefront of this growth as the market will shift from laptop to smart phone based solutions. New age analytics solutions like using CCTV for eyeball tracking, Planogram optimisation, single view of customer to create shopper profile and anticipate needs better, analysing supplier and employee performance and compliance (attrition analytics, workforce planning), are all seeing an uptake in the Indian market.

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.


Tags assigned to this article:
digital analytics Customer engagement Cashless payments

Sudipta Ghosh

Partner, Data and Analytics PwC India

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